Convert structured array with various numeric data types to regular array

Question

Suppose I have a NumPy structured array with various numeric datatypes. As a basic example,

my_data = np.array( [(17, 182.1),  (19, 175.6)],  dtype='i2,f4')

How can I cast this into a regular NumPy array of floats?

From this answer, I know I could use

np.array(my_data.tolist())

but apparently it is slow since you "convert an efficiently packed NumPy array to a regular Python list".

Answer 1

You can do it easily with Pandas:

>>> import pandas as pd
>>> pd.DataFrame(my_data).values
array([[  17.       ,  182.1000061],
       [  19.       ,  175.6000061]], dtype=float32)